EXPLORING NON-INVASIVE DISEASE BIOMARKERS WITH URINARY OMICS ANALYSIS.

Exploring Noninvasive Disease Biomarkers with Urinary Omics Analysis offers a transformative journey into the world of non-invasive diagnostics. This comprehensive volume delves into the molecular foundations of urinary biomarkers, illuminating the intricate signatures that indicate various patholog...

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Bibliographic Details
Corporate Author:	ScienceDirect (Online service)
Format:	eBook
Language:	English
Published:	[S.l.] : Academic Press, 2025.
Subjects:	Biochemical markers. Diagnosis, Noninvasive. Urinary organs > Diseases > Diagnosis. Biomarkers Marqueurs biologiques. Diagnostics > Méthodes non effractives. Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Front Cover
Exploring Noninvasive Disease Biomarkers with Urinary Omics Analysis
Copyright Page
Contents
List of contributors
Foreword
Preface
1 Molecular foundations of urinary biomarkers
1.1 Introduction
1.2 Urinary biomarker discovery
1.3 Exploration of urinary biomarkers identified
1.4 Different types of urinary biomarkers
1.4.1 Protein urinary biomarkers
1.4.2 Urinary gene biomarkers
1.4.3 Urinary electrolyte biomarker
1.4.4 Metabolites as urinary biomarkers
1.4.5 Urinary biomarkers of extracellular vesicles
1.5 Role of urine biomarkers in disease diagnosis
1.5.1 Cancer
1.5.1.1 Bladder cancer
1.5.1.2 Prostate cancer
1.5.1.3 Nonurological cancers
1.5.1.4 Cervical cancer
1.5.2 Kidney diseases
1.5.3 Respiratory diseases
1.5.4 Cardiovascular diseases
1.5.5 Neurodegenerative disorders
1.5.6 Diabetes mellitus
1.5.7 Cerebrovascular disease
1.5.8 Trauma
1.5.9 Coagulation disease
1.6 Molecular pathways of urinary biomarker expression
1.7 Analytical techniques for urine biomarkers analysis and validation
1.7.1 Mass spectroscopy
1.7.2 Immunoassay
1.7.3 Capillary electrophoresis
1.7.4 Nuclear magnetic resonance spectroscopy
1.7.5 High-performance liquid chromatography
1.7.6 Polymerase chain reaction and next-generation sequencing
1.8 Point-of-care of urinalysis
1.9 Clinical applications, challenges, and future directions
1.10 Conclusions
Abbreviations
References
2 Analytical technology: innovations in urinary biomarker discovery
2.1 Introduction
2.2 Origin of urine biomarkers
2.2.1 Sources of urine biomarkers
2.2.2 Types of urine biomarkers
2.3 Analytical technologies
2.3.1 UV-Visible spectroscopy
2.3.1.1 Applications
2.3.1.1.1 Identifying metabolic by-products
2.3.1.1.2 Analysis of proteins.
2.3.1.1.3 Monitoring of substance use
2.3.1.1.4 The identification of abnormal alterations
2.3.1.2 Advantages
2.3.1.3 Disadvantages
2.3.2 Hydrophilic interaction liquid chromatography
2.3.2.1 Applications
2.3.2.1.1 Drug metabolomics and pharmacokinetics
2.3.2.1.2 Environmental and toxicological studies
2.3.2.1.3 Nutritional biomarkers
2.3.2.1.4 Forensic toxicology
2.3.2.2 Advantages
2.3.2.3 Disadvantages
2.3.3 Mass spectrometry
2.3.3.1 Ion source
2.3.3.2 Mass analyzer
2.3.3.3 Detector
2.3.3.4 Applications
2.3.3.4.1 Metabolomics
2.3.3.4.2 Proteomics and peptidomics
2.3.3.4.3 Liquid biopsy
2.3.3.4.4 Pediatric and neonatal biomarkers
2.3.3.4.5 Environmental exposure assessment
2.3.3.5 Advantages
2.3.3.6 Disadvantages
2.4 Proteomics
2.4.1 Goals of proteomics
2.4.2 Methodology for the proteomic analysis of urine biomarkers
2.4.2.1 Liquid chromatography?mass spectrometry
2.4.2.2 Another technique called two-dimensional gel electrophoresis
2.4.2.3 Western blotting
2.4.2.4 Protein microarrays
2.4.2.5 The enzyme-linked immunosorbent assay
2.4.2.6 Stable isotope labeling with amino acids in cell culture
2.4.2.7 Isobaric tags for relative and absolute quantification
2.4.2.8 Surface enhanced laser desorption/ionization (SELDI) a modified form of matrix-assisted laser desorption/ionization
2.4.2.9 Capillary electrophoresis
2.4.2.10 Bioinformatics
2.4.2.11 Urine proteomic analysis workflow involves collecting and preparing samples
2.4.2.12 Applications
2.4.2.12.1 COVID-19 assessing diagnosis and severity
2.4.2.12.2 Emphasizing microbiome health
2.4.2.12.3 Mental health
2.4.2.12.4 Identifying biomarkers
2.4.2.12.5 Urine biomarkers are also being explored to diagnose and manage rare disorders
2.4.2.13 Advantages.
2.4.2.14 Disadvantages
2.5 Metabolomics
2.5.1 Integrated analytical techniques
2.5.1.1 Applications of metabolomics in urine biomarker analysis
2.5.1.1.1 Disease biomarker discovery
2.5.1.1.2 Metabolic disorders
2.5.1.1.3 Environmental and toxicological exposure
2.5.1.1.4 Infectious diseases
2.5.1.2 Advantage
2.5.1.3 Disadvantages
2.6 Multiomics
2.6.1 Applications
2.6.1.1 Cancer
2.6.1.2 Kidney disorder
2.6.1.3 Cardiovascular disease
2.6.1.4 Neurodegenerative disorders
2.6.1.5 Osteoporosis
2.6.2 Advantage
2.6.3 Disadvantages
2.7 Microbiome profiling
2.7.1 Key aspects
2.7.1.1 Microbial species identification
2.7.1.2 Functional analysis
2.7.1.3 Advantages
2.7.1.4 Disadvantages
2.8 Enzyme-linked immunosorbent assay
2.8.1 Types of enzyme-linked immunosorbent assay
2.8.1.1 General methodology
2.8.1.2 Applications
2.8.1.3 Advantages
2.8.1.4 Disadvantages
2.9 Multiplex protein detection immunoassay
2.9.1 Applications
2.9.2 Advantages
2.9.3 Disadvantages
2.10 Single antibody array chips
2.10.1 Working
2.10.1.1 Applications
2.10.1.2 Advantages
2.10.1.3 Disadvantages
2.11 Advanced statistical methodologies
2.11.1 Statistical techniques and their applications
2.11.1.1 Multivariate analysis
2.11.1.2 Machine learning algorithms
2.11.1.3 Bayesian inference
2.11.2 Software tools
2.11.3 Visualization tools
2.12 Conclusion
AI disclosure
References
3 Infectious disease diagnostics: insights from urinary omics
3.1 Introduction
3.2 The emergence of urinary omics as an infectious disease diagnostic tool
3.3 Scope and impact of urinary omics on infectious disease detection
3.4 Technological advancements in urinary omics
3.4.1 High-throughput sequencing and metabolomic profiling techniques.
3.4.2 Innovations in bioinformatics for data analysis and interpretation
3.4.3 Integration of omics data: a multidimensional approach
3.5 Pathogen detection and biomarker identification
3.5.1 Strategies for pathogen-specific biomarker discovery
3.5.2 Characterization of host response signatures to infection
3.5.3 Differential biomarker expression and pathogenicity
3.6 Clinical case studies: urinary omics in action
3.6.1 Case studies
3.6.1.1 Recurrent urinary tract infections studied using urinary omics approaches
3.6.1.1.1 Genomic insights into recurrent urinary tract infections
3.6.1.1.2 Proteomic analysis of recurrent urinary tract infections
3.6.1.1.3 Metabolomic profiling in recurrent urinary tract infections
3.6.1.1.4 Microbiomic contributions to recurrent urinary tract infections
3.6.1.1.5 Integrative omics approaches to recurrent urinary tract infections
3.6.1.2 Tuberculosis studied using urinary omics approaches
3.6.1.2.1 Genomic insights into tuberculosis using urinary samples
3.6.1.2.2 Proteomic analysis of urine in tuberculosis
3.6.1.2.3 Metabolomic profiling in tuberculosis
3.6.1.2.4 Microbiomic contributions to tuberculosis diagnosis and management
3.6.1.2.5 Integrative omics approaches
3.6.1.3 COVID-19 studied using urinary omics approaches
3.6.1.3.1 Genomic insights into COVID-19 using urinary samples
3.6.1.3.2 Proteomic analysis of urine in COVID-19
3.6.1.3.3 Metabolomic profiling in COVID-19
3.6.1.3.4 Microbiomic contributions to COVID-19 diagnosis and management
3.6.1.3.5 Integrative omics approaches
3.6.2 Comparative analysis with traditional diagnostic methods
3.6.3 Urinary omics in emerging and reemerging infectious diseases
3.7 Challenges and considerations in urinary omics diagnostics
3.7.1 Sample collection and standardization issue.
3.7.2 Sensitivity, specificity, and predictive value of omics-based tests
3.7.2.1 Sensitivity and specificity challenges
3.7.2.2 Standardization and biomarker degradation
3.7.2.3 Bioinformatics and predictive value
3.7.3 Ethical, legal, and social implications of omics data
3.7.3.1 Ethical considerations
3.7.3.2 Legal implications
3.7.3.3 Social implications
3.8 Future directions and potential of urinary omics
3.8.1 Next-generation technologies and their prospective impact
3.8.2 Bridging the gap between research and clinical practice
3.8.3 Global health perspectives and accessibility of omics diagnostics
3.9 Conclusion
AI disclosure
References
4 Standardizing sample preparation: ensuring integrity in urinary omics
4.1 Introduction
4.2 Sample preparation and preprocessing
4.2.1 Processing of urine samples
4.2.2 Optimizing omics research practices
4.2.3 Heel stick sample
4.2.4 Impact of external factors on sample integrity
4.2.4.1 Temperature
4.2.4.2 pH
4.2.4.3 Time
4.2.4.4 Other parameters
4.2.5 Strategies for minimizing preanalytical variability
4.3 Sample processing
4.3.1 Metabolic quenching in urinary omics
4.3.2 Centrifugation and filtration in Extracellular Vesicles (EV) isolation
4.3.3 Aliquoting and storage
4.3.4 Thawing of samples
4.3.5 Quality control measures
4.4 Analytical techniques for diagnosing urinary problems
4.4.1 Overview of urinary omics analytical techniques
4.4.2 Pros and cons
4.4.2.1 Limitations of surface-enhanced laser desorption/ionization-TOF mass spectrometry
4.4.2.2 Limitations of capillary electrophoresis-mass spectrometry in urinary proteomics
4.4.3 Considerations for sample preparation
4.5 Data analysis
4.5.1 Overview of data analysis techniques
4.5.2 Quality control measures.